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Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies

Summary: An analysis of gene set [e.g. Gene Ontology (GO)] enrichment assumes that all genes are sampled independently from each other with the same probability. These assumptions are violated in genome-wide association (GWA) studies since (i) longer genes typically have more single-nucleotide polym...

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Autores principales: Kofler, Robert, Schlötterer, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3400962/
https://www.ncbi.nlm.nih.gov/pubmed/22635606
http://dx.doi.org/10.1093/bioinformatics/bts315
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author Kofler, Robert
Schlötterer, Christian
author_facet Kofler, Robert
Schlötterer, Christian
author_sort Kofler, Robert
collection PubMed
description Summary: An analysis of gene set [e.g. Gene Ontology (GO)] enrichment assumes that all genes are sampled independently from each other with the same probability. These assumptions are violated in genome-wide association (GWA) studies since (i) longer genes typically have more single-nucleotide polymorphisms resulting in a higher probability of being sampled and (ii) overlapping genes are sampled in clusters. Herein, we introduce Gowinda, a software specifically designed to test for enrichment of gene sets in GWA studies. We show that GO tests on GWA data could result in a substantial number of false-positive GO terms. Permutation tests implemented in Gowinda eliminate these biases, but maintain sufficient power to detect enrichment of GO terms. Since sufficient resolution for large datasets requires millions of permutations, we use multi-threading to keep computation times reasonable. Availability and implementation: Gowinda is implemented in Java (v1.6) and freely available on http://code.google.com/p/gowinda/ Contact: christian.schloetterer@vetmeduni.ac.at Supplementary information: Manual: http://code.google.com/p/gowinda/wiki/Manual. Test data and tutorial: http://code.google.com/p/gowinda/wiki/Tutorial. Validation: http://code.google.com/p/gowinda/wiki/Validation.
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spelling pubmed-34009622012-07-20 Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies Kofler, Robert Schlötterer, Christian Bioinformatics Applications Note Summary: An analysis of gene set [e.g. Gene Ontology (GO)] enrichment assumes that all genes are sampled independently from each other with the same probability. These assumptions are violated in genome-wide association (GWA) studies since (i) longer genes typically have more single-nucleotide polymorphisms resulting in a higher probability of being sampled and (ii) overlapping genes are sampled in clusters. Herein, we introduce Gowinda, a software specifically designed to test for enrichment of gene sets in GWA studies. We show that GO tests on GWA data could result in a substantial number of false-positive GO terms. Permutation tests implemented in Gowinda eliminate these biases, but maintain sufficient power to detect enrichment of GO terms. Since sufficient resolution for large datasets requires millions of permutations, we use multi-threading to keep computation times reasonable. Availability and implementation: Gowinda is implemented in Java (v1.6) and freely available on http://code.google.com/p/gowinda/ Contact: christian.schloetterer@vetmeduni.ac.at Supplementary information: Manual: http://code.google.com/p/gowinda/wiki/Manual. Test data and tutorial: http://code.google.com/p/gowinda/wiki/Tutorial. Validation: http://code.google.com/p/gowinda/wiki/Validation. Oxford University Press 2012-08-01 2012-05-26 /pmc/articles/PMC3400962/ /pubmed/22635606 http://dx.doi.org/10.1093/bioinformatics/bts315 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Kofler, Robert
Schlötterer, Christian
Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
title Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
title_full Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
title_fullStr Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
title_full_unstemmed Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
title_short Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
title_sort gowinda: unbiased analysis of gene set enrichment for genome-wide association studies
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3400962/
https://www.ncbi.nlm.nih.gov/pubmed/22635606
http://dx.doi.org/10.1093/bioinformatics/bts315
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